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ICDM
2005
IEEE
168views Data Mining» more  ICDM 2005»
13 years 10 months ago
A Scalable Collaborative Filtering Framework Based on Co-Clustering
Collaborative filtering-based recommender systems, which automatically predict preferred products of a user using known preferences of other users, have become extremely popular ...
Thomas George, Srujana Merugu
SIGIR
2000
ACM
13 years 8 months ago
SWAMI: a framework for collaborative filtering algorithm development and evaluation
We present a Java-based framework, SWAMI (Shared Wisdom through the Amalgamation of Many Interpretations) for building and studying collaborative filtering systems. SWAMI consist...
Danyel Fisher, Kris Hildrum, Jason I. Hong, Mark W...
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
14 years 4 months ago
Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...
ISMIS
2005
Springer
13 years 9 months ago
Incremental Collaborative Filtering for Highly-Scalable Recommendation Algorithms
Most recommendation systems employ variations of Collaborative Filtering (CF) for formulating suggestions of items relevant to users’ interests. However, CF requires expensive co...
Manos Papagelis, Ioannis Rousidis, Dimitris Plexou...
TKDD
2010
121views more  TKDD 2010»
13 years 2 months ago
Factor in the neighbors: Scalable and accurate collaborative filtering
Recommender systems provide users with personalized suggestions for products or services. These systems often rely on Collaborating Filtering (CF), where past transactions are ana...
Yehuda Koren